Loading Data

strom_rpca <- readRDS(file.path(PATH, "data/sc/strom_rpca_subset.rds"))

Annotations

strom_rpca$celltypist_strom_only <- with(strom_rpca@meta.data, 
                                     case_when(celltypist_broad == "Stromal" ~ celltypist_pred,
                                               .default = celltypist_broad))
strom_rpca$singler_strom_only <- with(strom_rpca@meta.data, 
                                     case_when(singleR_broad == "Stromal" ~ singler_pred,
                                               .default = singleR_broad))
strom_rpca$author_strom_only <- with(strom_rpca@meta.data, 
                                     case_when(author_broad == "Stromal" ~ celltype_new,
                                               .default = author_broad))
Idents(strom_rpca) <- strom_rpca$RNA_snn_res.0.4
p1 <- DimPlot_scCustom(strom_rpca,
                       reduction = "umap.rpca",
                       group.by = "RNA_snn_res.0.4",
                       label = TRUE,
                       label.size = 3,
                       repel = TRUE, 
                       raster = FALSE) + labs(title = "Clustering (0.4)", x = "UMAP 1", y = "UMAP 2")
p2 <- DimPlot_scCustom(strom_rpca,
                       reduction = "umap.rpca",
                       group.by = "celltypist_strom_only",
                       label = TRUE,
                       label.size = 1.5,
                       label.box = TRUE,
                       repel = TRUE, 
                       raster = FALSE) + 
  labs(title = "Celltypist", x = "UMAP 1", y = "UMAP 2") +
  theme(legend.position = "none")
p3 <- DimPlot_scCustom(strom_rpca,
                       reduction = "umap.rpca",
                       group.by = "singler_strom_only",
                       label = TRUE,
                       label.size = 1.5,
                       label.box = TRUE,
                       repel = TRUE, 
                       raster = FALSE) + 
  labs(title = "SingleR", x = "UMAP 1", y = "UMAP 2") +
  theme(legend.position = "none")
p4 <- DimPlot_scCustom(strom_rpca,
                       reduction = "umap.rpca",
                       group.by = "author_strom_only",
                       label = TRUE,
                       label.size = 1.5,
                       label.box = TRUE,
                       repel = TRUE, 
                       raster = FALSE) + 
  labs(title = "Author", x = "UMAP 1", y = "UMAP 2") +
  theme(legend.position = "none")
combined <- cowplot::plot_grid(p1, p2, p3, p4, ncol = 2, nrow = 2)
ggsave(plot = combined, filename = file.path(PATH, "results/umaps/stromal_rpca_annot_04.png"), height = 8, width = 9)
combined

Loading markers

endothelial <- c("PLVAP", "CLDN5")
mural <- c("RGS5", "ACTA2", "PDGFRB")
fibroblasts <- c("COL1A1", "DCN", "LUM")
mesothelial <- c("KRT19", "MSLN", "CALB2")
prolif_stromal <- c("STMN1", "TOP2A", "MKI67")
glial <- c("GPM6B", "CDH19")

pan_cancer_stromal_sigs <- readRDS(file.path(PATH, "data/signatures/stromal/ye_2024/pan_cancer_stromal_sigs.rds"))
pan_cancer_stromal_sigs <- lapply(pan_cancer_stromal_sigs, function(x) x[x %in% rownames(strom_rpca)])

strom_sigs <- readRDS(file.path(PATH, "/data/signatures/stromal/wu_embo_2020/strom_sigs.rds"))
strom_sigs <- lapply(strom_sigs, function(x) x[x %in% rownames(strom_rpca)])

Endothelial

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = endothelial)

Endothelial subpopulations

names(pan_cancer_stromal_sigs)[str_detect(names(pan_cancer_stromal_sigs), "ECs")]
##  [1] "Aerocytes ECs"        "Arterial ECs"         "CD14+ circECs"       
##  [4] "Capillaries ECs"      "FOS+ Capillaries ECs" "ISG15+ ECs"          
##  [7] "Immature ECs"         "Lymphatics ECs"       "Venous ECs"          
## [10] "Venous IL6+ ECs"
ec_sub_sigs <- pan_cancer_stromal_sigs[str_detect(names(pan_cancer_stromal_sigs), "ECs")]
ec_sub_sigs_top4 <- lapply(ec_sub_sigs, function(x) x[1:4])

Aerocytes ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`Aerocytes ECs`)

Arterial ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`Arterial ECs`)

CD14+ circECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`CD14+ circECs`)

Capillaries ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`Capillaries ECs`)

FOS+ Capillaries ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`FOS+ Capillaries ECs`)

ISG15+ ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`ISG15+ ECs`)

Immature ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`Immature ECs`)

Lymphatic ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`Lymphatics ECs`)

Venous ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`Venous ECs`)

Venous IL6+ ECs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = ec_sub_sigs_top4$`Venous IL6+ ECs`)

Mural Cells

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural)

Mural subpopulations

names(pan_cancer_stromal_sigs)[str_detect(names(pan_cancer_stromal_sigs), "SMCs|PCs")]
##  [1] "ATF3+ PCs"       "ATF3+ SMCs"      "CCL19+ PCs"      "ECM PCs"        
##  [5] "FABP4+ PCs"      "Fibrogenic PCs"  "HTRA3+ PCs"      "ISG15+ PCs"     
##  [9] "RERGL high SMCs" "RERGL low SMCs"  "SERPINE1+ PCs"   "Vascular PCs"
mural_sub_sigs <- pan_cancer_stromal_sigs[str_detect(names(pan_cancer_stromal_sigs), "SMCs|PCs")]
mural_sub_sigs_top4 <- lapply(mural_sub_sigs, function(x) x[1:4])

iPVL

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = strom_sigs$ipvl[1:4])

dPVL

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = strom_sigs$dpvl[1:4])

ATF3+ PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`ATF3+ PCs`)

ATF3+ SMCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`ATF3+ SMCs`)

CCL19+ PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`CCL19+ PCs`)

ECM PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`ECM PCs`)

FABP4+ PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`FABP4+ PCs`)

Fibrogenic PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`Fibrogenic PCs`)

HTRA3+ PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`HTRA3+ PCs`)

ISG15+ PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`ISG15+ PCs`)

RERGL high SMCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`RERGL high SMCs`)

RERGL low SMCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`RERGL low SMCs`)

SERPINE1+ PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`SERPINE1+ PCs`)

Vascular PCs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mural_sub_sigs_top4$`Vascular PCs`)

Fibroblast Cells

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fibroblasts)

Fibroblast subpopulations

names(pan_cancer_stromal_sigs)[str_detect(names(pan_cancer_stromal_sigs), "Fib|CAFs")]
##  [1] "ADAMDEC1+ TrsFib" "ATF3+ PanFib"     "CA12+ CAFs"       "CCL19+ Fib"      
##  [5] "COL11A1+ CAFs"    "DPT+ PanFib"      "IL6+ iCAFs"       "ISG15+ CAFs"     
##  [9] "LAMP5+ CAFs"      "MYH11+ myoFib"    "NPNT+ TrsFib"     "PI16+ PanFib"    
## [13] "SFRP4+ CAFs"      "SOX6+ TrsFib"     "Fibrogenic PCs"
fib_sub_sigs <- pan_cancer_stromal_sigs[str_detect(names(pan_cancer_stromal_sigs), "Fib|CAFs")]
fib_sub_sigs_top4 <- lapply(fib_sub_sigs, function(x) x[1:4])

myCAFs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = strom_sigs$mycafs[1:4])

iCAFs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = strom_sigs$icafs[1:4])

ADAMDEC1+ TrsFib

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`ADAMDEC1+ TrsFib`)

ATF3+ PanFib

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`ATF3+ PanFib`)

CA12+ CAFs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`CA12+ CAFs`)

CCL19+ Fib

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`CCL19+ Fib`)

COL11A1+ CAFs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`COL11A1+ CAFs`)

DPT+ PanFib

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`DPT+ PanFib`)

IL6+ iCAFs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`IL6+ iCAFs`)

ISG15+ CAFs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`ISG15+ CAFs`)

LAMP5+ CAFs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`LAMP5+ CAFs`)

MYH11+ myoFib

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`MYH11+ myoFib`)

NPNT+ TrsFib

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`NPNT+ TrsFib`)

PI16+ PanFib

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`PI16+ PanFib`)

SFRP4+ CAFs

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`SFRP4+ CAFs`)

SOX6+ TrsFib

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = fib_sub_sigs_top4$`SOX6+ TrsFib`)

Mesothelial Cells

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = mesothelial)

Prolif. Stromal Cells

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = prolif_stromal)

Glial Cells

Plot_Density_Custom(strom_rpca, reduction = "umap.rpca", features = glial)